Existing systems provide resource management for a plurality of virtual machines (VMs). For example, some of the existing systems provide reactive management by responding to changes in demand that have already occurred. These reactive management systems perform load balancing operations on a cluster of virtualized hosts based on collected statistics and state information. Such reactive management systems, however, may struggle to handle spikes in demand at least because of the delay incurred in performing the load balancing operations (e.g., moving VMs or VM disks among hosts). For example, the load balancing operations may include hundreds of serialized and/or parallel migrations such as moving VMs and/or VM disks among hosts. The cost of these migrations is higher when the VMs are heavily loaded than when lightly loaded at least because memory associated with the VMs may be changed frequently when heavily loaded.
Other existing systems provide proactive management by predicting changes in demand and performing the load balancing operations in advance of the predicted changes. The proactive management systems, however, may suffer from inaccurate demand predictions thus rendering some of the completed load balancing operations unnecessary. Performing unnecessary load balancing operations before the predicted changes in demand incurs a present cost that may have a negative impact on the performance of current workloads. For example, quality of service expectations may be violated.